搜索结果: 1-15 共查到“经济统计学 processes”相关记录17条 . 查询时间(0.093 秒)
Law of large numbers for branching symmetric Hunt processes with measure-valued branching rates
Law of large numbers branching Hunt processes spine approach h-transform spectral gap
2016/1/26
We establish weak and strong law of large numbers for a class of branching symmetric Hunt processes with the branching rate being a smooth measure with respect to the underlying Hunt process, and the ...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/26
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Central Limit Theorems for Supercritical Branching Nonsymmetric Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale
2016/1/25
In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms sati...
Central Limit Theorems for Supercritical Branching Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale eigenfunction expansion
2016/1/25
In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations o...
Bessel Processes, Stochastic Volatility, and Timer Options
Bessel Processes Stochastic Volatility Timer Options
2016/1/25
Motivated by analytical valuation of timer options (an important innovation in realized variance based derivatives), we explore their novel mathematical connection with stochastic volatility and Besse...
Central Limit Theorems for Supercritical Branching Markov Processes
Central limit theorem branching Markov process supercritical
2016/1/20
In this paper we establish spatial central limit theorems for a large class of supercritical branching Markov processes with general spatial-dependent branching mechanisms. These are generalizations o...
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/20
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Bessel Processes, Stochastic Volatility, and Timer Options
Bessel Processes Stochastic Volatility Timer Options
2016/1/20
Motivated by analytical valuation of timer options (an important innovation in realized variance based derivatives), we explore their novel mathematical connection with stochastic volatility and Besse...
On the Approximate Maximum Likelihood Estimation for Diffusion Processes
Asymptotic expansion Asymptotic normality Consistency Dis- crete time observation Maximum likelihood estimation
2016/1/19
The transition density of a diffusion process does not admit an explicit expression in general, which prevents the full maximum likelihood estimation (MLE) based on discretely observed sample paths. A...
Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions
Conditional characteristic function Diffusion processes Empirical likelihood Kernel smoothing L′ evy driven processes
2016/1/19
Markov processes are used in a wide range of disciplines including finance.The transition densities of these processes are often unknown. However, the conditionalcharacteristic functions are more like...
Information Symmetries in Irreversible Processes
stochastic process reversibility irreversibility hidden Markov model
2011/7/19
We study dynamical reversibility in stationary stochastic processes from an information theoretic perspective. Extending earlier work on the reversibility of Markov chains, we focus on finitary proces...
Expectiles for subordinated Gaussian processes with applications
expectiles robustness local shift sensitivity
2011/7/19
In this paper, we introduce a new class of estimators of the Hurst exponent of the fractional Brownian motion (fBm) process.
The beta-Bernoulli process provides a Bayesian nonparametric prior for models involving collections of binary-valued features.
Analytic Loss Distributional Approach Model for Operational Risk from the alpha-Stable Doubly Stochastic Compound Processes and Implications for Capital Allocation
Operational Risk Loss Distributional Approach Doubly stochastic Poisson Process -Stable Basel II Solvency II
2011/3/25
Under the Basel II standards, the Operational Risk (OpRisk) advanced measurement approach is not prescriptive regarding the class of statistical model utilised to undertake capital estimation. It has ...
Mixing properties of ARCH and time-varying ARCH processes
2-mixing absolutely regular (β-mixing) ARCH(∞) conditional densities strong mixing (α-mixing) time-varying ARCH
2011/3/21
There exist very few results on mixing for non-stationary processes. However, mixing is often required in statistical inference for non-stationary processes such as time-varying ARCH (tvARCH) models. ...